code: def setup_device(current_gpu_index, num_gpus):
      # Device setup
      os.environ["MASTER_ADDR"] = "localhost"
      os.environ["MASTER_PORT"] = "56492"
      device = torch.device("cuda:{}".format(current_gpu_index))
      torch.distributed.init_process_group(
          backend="nccl",
          init_method="env://",
          world_size=num_gpus,
          rank=current_gpu_index,
      )
      torch.cuda.set_device(device)
  
file_path: keras/guides/distributed_training_with_torch.py
imports: import os
  import torch
  import numpy
  import keras
label_desc: Use image node_id 4 for calling a global function with example usage: setup_device(current_gpu_index, num_gpus) without return types